Edentulism as an Independent Risk Factor for Sarcopenia: Evidence from Cross-sectional and Longitudinal Analyses Based on the CHARLS Cohort

Edentulism as an Independent Risk Factor for Sarcopenia: Evidence from Cross-sectional and Longitudinal Analyses Based on the CHARLS Cohort | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Edentulism as an Independent Risk Factor for Sarcopenia: Evidence from Cross-sectional and Longitudinal Analyses Based on the CHARLS Cohort Zhai Tianyang, Sun ZhongYi, Xie QianYang, Wu YanHui, Zou Huiru, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6637114/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Dec, 2025 Read the published version in BMC Oral Health → Version 1 posted 11 You are reading this latest preprint version Abstract Background Edentulism and sarcopenia are two highly prevalent, age-related conditions that share common nutritional, inflammatory, and functional pathways. Whether tooth loss independently contributes to the development of sarcopenia—and in which population strata this effect is strongest—remains uncertain, especially in Asian cohorts. Methods We analysed 17,099 participants (baseline 2011) from the China Health and Retirement Longitudinal Study (CHARLS). Sarcopenia was defined by Asian Working Group for Sarcopenia 2019 criteria. Multivariable logistic models (wave 1 cross-sectional) and Cox models (waves 1–3 longitudinal, seven-year follow-up) were fitted sequentially: Model 1 (crude), Model 2 (plus demographic covariates), Model 3 (plus metabolic/ inflammatory factors). Propensity-score matching (PSM) was applied to minimise selection bias. Subgroup analyses covered sex, residence, marital status, education, smoking, drinking, and region. Sensitivity analyses tested robustness. Results Edentulism prevalence was 8.8%; sarcopenia prevalence, 15.0%. Cross-sectionally, edentulism increased sarcopenia risk in Model 1 (β = 1.359, P < 0.001) and remained significant after full adjustment (β = 0.271, P = 0.023). In the PSM set, the effect strengthened (Model 3 β = 0.453, P = 0.004). Longitudinally, edentulism predicted incident sarcopenia (Model 1 β = 1.109, P < 0.001); significance attenuated after full adjustment (β = 0.070, P = 0.221) but re-emerged in PSM analyses (β = 0.193, P = 0.008). Subgroup analyses showed consistently higher risks in males, rural residents, low-education groups, non-smokers, non-drinkers, and western regions. Conclusions Edentulism is a robust, independent marker of elevated sarcopenia risk in Chinese adults, with particularly strong effects in socio-economically vulnerable subgroups. Routine oral-health screening should be integrated into geriatric assessments to identify patients at high risk for sarcopenia. edentulism sarcopenia oral health ageing longitudinal cohort propensity-score matching Figures Figure 1 1 Background With the acceleration of global population aging, China has become one of the countries with the largest elderly population and fastest aging rate. According to the "China Aging Career Development Report (2024)," China's population aged 60 and above has reached 280 million, accounting for over 20% of the total population. Against this backdrop, age-related chronic diseases and functional decline issues have become increasingly prominent. Among them, edentulism and sarcopenia, two geriatric syndromes with high prevalence but often overlooked, are seriously affecting the quality of life and healthy life expectancy of older adults[ 1 – 3 ]. Edentulism (complete tooth loss) is prevalent among older Chinese adults. National oral health epidemiological survey data show that the prevalence of edentulism among adults aged 65–74 years reaches 8.7%, with rates exceeding 12% in rural areas [ 4 – 6 ]. Tooth loss not only directly leads to decreased masticatory function but may also indirectly increase the risk of various systemic diseases by limiting dietary choices, inducing malnutrition, and creating chronic inflammatory states [ 7 – 9 ]. Meanwhile, sarcopenia (characterized by progressive decline in muscle mass, strength, and function) has a prevalence of approximately 10%-15% among community-dwelling older adults and is significantly associated with falls, fractures, functional disability, and mortality risk [ 3 , 10 ]. Studies indicate that all-cause mortality rates within five years are 1.5–2.3 times higher in sarcopenia patients compared to healthy populations [ 11 – 13 ], with disease burden exceeding that of traditional chronic conditions such as hypertension and diabetes. In recent years, although research has begun to focus on the relationship between oral health and muscle function, these studies have notable limitations, such as insufficient sample representativeness [ 14 – 16 ]. As a country with deep aging trends and significant regional differences, China urgently needs empirical research with national representativeness. Furthermore, existing research designs are predominantly cross-sectional, unable to establish causal relationships between edentulism and sarcopenia, and inadequately control for potential confounding factors such as socioeconomic status and comorbidities. Notably, although both edentulism and sarcopenia are closely related to aging, the potential associative mechanisms between them have not been systematically explored. Addressing the evidence gap in research on the association between edentulism and sarcopenia among Chinese older adults, this study integrates multiple waves of longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS) from 2011–2020[ 17 ]. Through cross-sectional analysis, we reveal the prevalence association between edentulism and sarcopenia and its differential patterns across urban-rural, gender, and regional dimensions. Based on the 2011 baseline population without sarcopenia, we conduct a 7-year follow-up to assess the long-term impact of edentulism on sarcopenia incidence risk. The research findings will promote the inclusion of oral health indicators in comprehensive geriatric assessment systems, drive the development of evidence-based nutritional intervention strategies, and provide theoretical foundations for establishing an integrated "oral-muscular" health management framework, thereby effectively addressing major public health challenges brought by population aging. 2 Materials and Methods 2.1 Research Design and Data Source This study employs an observational cohort design based on publicly available data from the CHARLS database. As a national cohort study covering 28 provinces in China, CHARLS systematically tracks changes in health, socioeconomic, and behavioral characteristics of middle-aged and older adults aged 45 and above. The project completed baseline survey (Wave 1) in 2011, with subsequent follow-ups every 2–3 years (2013, 2015, 2018, and 2020), comprehensively collecting multidimensional information including participants' demographic characteristics, health status, biomarkers (including blood tests), and functional assessments [ 17 ]. This research design integrates both cross-sectional and longitudinal analytical methods: the cross-sectional component evaluates the prevalence association patterns between edentulism and sarcopenia, while the longitudinal component follows individuals without sarcopenia at the 2011 baseline to track their risk of developing sarcopenia through 2018, thereby exploring the temporal relationship and potential mechanisms between these two geriatric syndromes. 2.2 Study Population and Sample Selection Inclusion criteria: (1) age ≥ 45 years; (2) complete oral examination records (for defining edentulism); (3) available muscle mass and strength measurement data (for diagnosing sarcopenia); (4) complete sociodemographic, health behavior, and comorbidity information at baseline (2011) and at least one follow-up. Exclusion criteria: (1) diagnosed with sarcopenia at baseline (for longitudinal analysis only); (2) missing key variables (such as grip strength, walking speed, number of teeth); (3) non-fasting status during blood sample collection. The final samples were used for cross-sectional and longitudinal analyses, ensuring adequate representativeness. 2.3 Variable Definitions and Measurements 2.3.1 Primary Exposure: Edentulism Edentulism was defined as having no natural teeth remaining in the oral cavity (complete tooth loss), assessed and confirmed through oral examination records from the CHARLS project. At baseline survey (Wave 1), variables wearing_dentures and fixed_or_removable were used to determine whether respondents wore dentures and the type of dentures; in subsequent follow-ups (Wave 2 to Wave 4), complete tooth loss was directly assessed. Based on these evaluations, edentulism status was set as a binary variable, where "0" indicated having teeth (partial or complete) and "1" indicated edentulism (complete tooth loss). 2.3.2 Outcome Variable: Sarcopenia This study assessed sarcopenia status according to the Asian Working Group for Sarcopenia (AWGS) standards, defined and calculated through the following steps[ 18 , 19 ]: ①. Muscle mass assessment: Appendicular skeletal muscle mass index (ASM) was calculated based on gender-specific formulas: ASM = 0.193 × weight(kg) + 0.107 × height(cm) − 4.157 × sex(male = 1; female = 2) − 0.037 × age(years) − 2.631. ASM_Ht2 = ASM / (height²) (height in meters) Low muscle mass was defined as ASM/Ht² < 6.88 kg/m² for men or ASM/Ht² < 5.69 kg/m² for women. ②. Muscle strength assessment: Grip strength level was determined by calculating the average of left and right hand grip strength measurements. Low grip strength was defined as < 28 kg for men or 12 seconds for five repeated chair stands or walking speed < 1 m/s. ④. Sarcopenia diagnosis criteria: Sarcopenia was diagnosed when low muscle mass occurred concurrently with either low grip strength or physical function impairment. This diagnostic method complies with the AWGS standard definition of sarcopenia, ensuring comparability with international sarcopenia research and clinical relevance. 2.3.3 Covariates and Confounding Factors This study comprehensively considered multiple potential confounding factors that might influence the association between edentulism and sarcopenia. For demographic variables, we included age, gender, residence type, marital status, and education level. Lifestyle factors included smoking status and alcohol consumption. Considering China's regional development disparities, we categorized participants into "Eastern," "Midland," and "Western" geographic regions based on regional variables. Additionally, health and metabolic indicators encompassed body mass index, waist circumference, triglycerides, high-density lipoprotein cholesterol, fasting blood glucose, blood pressure, and the inflammatory marker C-reactive protein, to comprehensively control for potential effects of metabolic and inflammatory status on the studied association. 2.4 Statistical Analysis 2.4.1 Cross-sectional Analysis This study first conducted descriptive statistical analysis, dividing the sample into two groups based on edentulism status. Continuous variables were presented as mean ± standard deviation or median (interquartile range), while categorical variables were presented as frequency (percentage). Between-group differences were evaluated using t-tests (for normally distributed continuous variables), Mann-Whitney U tests (for non-normally distributed continuous variables), or chi-square tests (for categorical variables), according to data distribution characteristics. In multivariate analysis, we constructed three progressively adjusted logistic regression models with sarcopenia (binary: yes/no) as the dependent variable and edentulism as the independent variable. Model 1 represented the unadjusted crude association analysis; Model 2 adjusted for basic demographic characteristics including age, gender, urban-rural residence, education level, and marital status; Model 3 further adjusted for lifestyle factors (smoking, alcohol consumption), regional classification, and metabolic and inflammatory indicators (waist circumference, triglycerides, high-density lipoprotein, fasting blood glucose, systolic pressure, diastolic pressure, and C-reactive protein) based on Model 2. All analytical results were presented as odds ratios (OR) with their 95% confidence intervals (CI) to assess the strength and direction of the cross-sectional association between edentulism and sarcopenia. 2.4.2 Longitudinal Analysis To explore the temporal relationship between edentulism and sarcopenia occurrence, Cox proportional hazards regression models were employed for longitudinal analysis. Using the baseline population without sarcopenia as the study cohort, follow-up time was defined as the number of years from baseline to event occurrence or observation endpoint, with the four survey waves corresponding to observation time points of 0, 2, 4, and 7 years. The outcome event was defined as new-onset sarcopenia (final_event = 1 indicating diagnosis of sarcopenia during any follow-up wave), with event time (final_time) recorded as the follow-up time point of first sarcopenia diagnosis; for participants without sarcopenia during follow-up, the time point of the last follow-up was recorded and treated as censored. The Cox model adjusted for the same variables as Model 3 in the cross-sectional analysis, with results presented as hazard ratios (HR) with their 95% confidence intervals. Additionally, we conducted two sensitivity analyses: first, excluding individuals with specific health issues at baseline to assess result robustness; second, using multiple imputation methods for variables with missing rates below 5% to reduce information bias. 2.4.3 Sensitivity Analysis In this study, propensity score matching (PSM) was performed using age, sex, residence, marital status, educational attainment, smoking status, drinking status, and regional category as covariates [ 20 ]. A 1:1 nearest neighbor matching method was applied to minimize confounding bias [ 21 ]. The matched data were subsequently analyzed using logistic regression and Cox proportional hazards models to evaluate the association between edentulism and the outcome variable, sarcopenia. 2.4.4 Subgroup Analysis Considering that population heterogeneity might affect the generalizability of research findings, this study conducted subgroup analyses for key demographic and lifestyle characteristics, including gender (male/female), residence type (urban/rural), marital status (married cohabiting/married separated/single), education level (primary school and below/middle school and above), smoking status (smoker/non-smoker), alcohol consumption status (non-drinker/light drinker/regular drinker), and regional classification (eastern/central/western). By incorporating interaction terms and evaluating their statistical significance, we explored differential patterns of association between edentulism and sarcopenia across different population characteristic strata. All statistical analyses were performed using R 4.3.3 and related statistical packages, with two-sided tests and significance level set at p < 0.05. 2.5 Ethical Statement The CHARLS study was approved by the Biomedical Ethics Committee of Peking University, and all participants signed written informed consent. This study uses publicly available anonymized data, which is exempt from ethical review. 3. Results 3.1 Baseline Characteristics A total of 17,099 participants were included in the baseline analysis (Table 1). Among them, 1,494 individuals were diagnosed with edentulism, accounting for 8.8% of the total sample, and 2,557 individuals were identified with sarcopenia, with a prevalence of 15.0%. Notably, the prevalence of sarcopenia was significantly higher among participants with edentulism (36.7%, 548/1494) compared to those without edentulism (12.9%, 2005/15478). Additionally, the prevalence of edentulism was significantly higher in individuals with sarcopenia than in those without (P < 0.001), suggesting a potential association between the two conditions. Regarding demographic characteristics, participants with sarcopenia were significantly older than those without (67.0 vs. 57.0 years, P < 0.001) and were more likely to reside in rural areas (72.7% vs. 59.7%, P < 0.001). Marital status also differed significantly between groups, with a higher proportion of single, divorced, or widowed individuals in the sarcopenia group (28.1% vs. 9.9%, P < 0.001). Educational attainment was lower in the sarcopenia group, with 89.8% having only elementary school education or below, compared to 63.3% in the non-sarcopenia group (P < 0.001). In terms of lifestyle factors, a higher proportion of participants in the sarcopenia group were non-smokers (68.5% vs. 55.9%, P < 0.001) and non-drinkers (82.0% vs. 66.8%, P < 0.001). Regionally, individuals with sarcopenia were more frequently from western regions (34.3% vs. 26.7%, P < 0.001). Metabolic and health-related indicators also differed significantly. Participants with sarcopenia had significantly lower BMI (19.7 vs. 24.3, P < 0.001), waist circumference (77.0 cm vs. 87.4 cm, P < 0.001), and triglyceride levels (94.7 vs. 109.7, P < 0.001), but higher HDL-C levels (55.7 vs. 47.6, P < 0.001). Systolic blood pressure was slightly higher in the sarcopenia group but did not reach statistical significance (128.5 vs. 127.0 mmHg, P = 0.053), whereas diastolic blood pressure was significantly lower (72.0 vs. 76.0 mmHg, P < 0.001). Interestingly, CRP levels were lower in the sarcopenia group compared to the non-sarcopenia group (0.9 vs. 1.1, P < 0.001), and fasting blood glucose levels were also significantly reduced (101.2 vs. 103.1 mg/dL, P < 0.001). In summary, these findings suggest a potential link between edentulism and sarcopenia, and reveal a distinct profile of socio-demographic and metabolic characteristics among individuals with sarcopenia, including older age, lower socioeconomic status, rural residence, and specific metabolic traits. 3.2 Cross-sectional Analysis In the cross-sectional analysis based on wave 1 data, a significant association was observed between edentulism and sarcopenia (Table 2). In the crude model (Model 1), individuals with edentulism had a significantly increased risk of sarcopenia compared to those without (β = 1.359, P < 0.001). After adjustment for demographic confounders (Model 2), the association remained statistically significant, though attenuated (β = 0.219, P = 0.018). Following further adjustment for metabolic variables—including waist circumference, triglycerides, HDL cholesterol, fasting glucose, blood pressure—and C-reactive protein levels (Model 3), the association persisted (β = 0.271, P = 0.023). In the PSM population, edentulism remained significantly associated with an increased risk of sarcopenia. In the crude PSM model (Model 1), the association was evident (β = 0.285, P < 0.001). After adjusting for demographic variables (Model 2), the effect size increased (β = 0.393, P < 0.001), and further adjustment for metabolic, blood pressure, and inflammatory indicators (Model 3) yielded a consistently stronger association (β = 0.453, P = 0.004), indicating a robust and progressive link between edentulism and sarcopenia. 3.3 Longitudinal Analysis In the longitudinal analysis across waves 1 to 3, a significant association was observed between edentulism and the risk of sarcopenia (Table 3). In the crude model (Model 1), edentulous individuals had a significantly higher risk of developing sarcopenia compared to those without edentulism (β = 1.109, P < 0.001). After adjusting for demographic covariates (Model 2), the association was attenuated but remained statistically significant (β = 0.143, P = 0.003). However, further adjustment for metabolic variables, including waist circumference, triglycerides, HDL cholesterol, fasting glucose, blood pressure, and C-reactive protein (Model 3), rendered the association non-significant (β = 0.070, P = 0.221). Following PSM, the association remained robust. Edentulism was still positively associated with sarcopenia risk in the crude PSM model (β = 0.217, P < 0.001), and this association persisted after adjusting for demographic (Model 2, β = 0.171, P = 0.004) and metabolic variables (Model 3, β = 0.193, P = 0.008), suggesting a stable and independent relationship. In the cross-sectional subgroup analysis, the association between edentulism and sarcopenia was generally consistent across different demographic groups, with some degree of heterogeneity (Figure 1). When stratified by sex, edentulism was associated with an increased risk of sarcopenia in both males and females, with a slightly stronger effect observed among males. Stratified by residence, the association remained significant among both rural and urban populations, but was more pronounced in rural residents. In marital status subgroups, the association weakened slightly among single, divorced, or widowed individuals compared to those married and living with a spouse, yet a positive trend was still observed. Stratification by education level revealed that individuals with elementary education or below exhibited a stronger association. Regarding smoking and drinking status, the association was more evident among non-smokers and non-drinkers. Regional analysis showed the most prominent association in western regions, with positive associations also observed in the midland and eastern regions.Overall, these findings suggest that edentulism is a robust risk factor for sarcopenia across various subgroups, although differences exist by sex, residence, education level, and lifestyle factors, highlighting the need for tailored intervention strategies. Detailed information for these results are provided in Table S1. 3.5 Wave 1-3 Longitudinal Subgroup Analysis Across progressively adjusted models, the positive association between edentulism and sarcopenia remained statistically significant in many subgroups, although attenuation of effect sizes was observed in Model 2 and Model 3 (Table S2): In the sex-stratified analysis, both men and women showed significant associations in Model 1. In women, the effect size slightly decreased across models but remained significant. In men, the association remained strong and significant even in Model 3. In residential subgroups, both urban and rural populations demonstrated significant associations in Model 1 and Model 2. The effect weakened in urban populations in Model 3 but remained statistically significant in rural groups. Marital status subgroups showed significant associations in “married cohabiting” and “married living separately” in Model 1 and 2. In Model 3, only the ‘married cohabiting’ subgroup retained statistical significance, possibly due to reduced statistical power or confounding in other groups. For educational level, individuals with elementary education or below maintained consistent significance across all models, while those with middle school or higher education only showed significance in Model 1, losing it in later models. In smoking and drinking subgroups, Model 1 revealed strong associations across all categories. Model 2 and 3 showed more stable associations in non-smokers and non-drinkers, suggesting potential behavioral effect modification. Regional analysis demonstrated that in Model 1, Eastern, Central, and Western regions all had significant associations. In Model 2 and Model 3, the Eastern region retained the strongest and most stable effect, while significance in other regions diminished. Overall, even after adjusting for demographic, metabolic, and inflammatory confounders, edentulism remained a robust and independent risk factor for sarcopenia across diverse population strata. 4. Discussion In this study, we utilized cross-sectional analysis, longitudinal cohort follow-up, and PSM methods to uncover a significant association between edentulism and sarcopenia, and further investigated the heterogeneity of this relationship across different demographic and metabolic subgroups. Our findings revealed that among 17,099 participants included in this analysis, the overall prevalence of edentulism was 8.8%, while sarcopenia prevalence reached 15.0%. Notably, the prevalence of edentulism was significantly higher among individuals with sarcopenia compared to those without. Both cross-sectional and longitudinal analyses consistently showed robust positive associations between edentulism and sarcopenia risk, and these associations remained significant across most models even after adjusting for various potential confounders, including demographic characteristics, metabolic indicators, and inflammatory markers. These results provide strong evidence for further exploring the biological mechanisms and public health intervention strategies linking oral health and muscle function decline. Results from crude to progressively adjusted models indicated some attenuation of the association between edentulism and sarcopenia; however, analyses following PSM adjustment conversely demonstrated a gradually strengthened relationship. This effect reached its peak in the cross-sectional analysis in Model 3. Similarly, in the longitudinal analysis following PSM adjustment, the association remained robust and independent. Subgroup analyses further highlighted that the risk effect of edentulism on sarcopenia was more pronounced among males, residents of western regions, individuals with elementary education or below, non-smokers, and non-drinkers. Although slightly weaker in single, divorced, or widowed individuals, the overall positive trend remained consistent. These findings suggest that the impact of edentulism on sarcopenia risk could be modified by socioeconomic status, lifestyle habits, and regional factors. To further clarify the stability of the association between edentulism and sarcopenia and potential confounding factors, we conducted longitudinal subgroup analyses. Results indicated a stronger and more consistent association effect among males compared to females across all models. Analyses by urban and rural residence demonstrated that the association in rural residents was consistently stronger and sustained across models compared to urban residents. Notably, participants with lower educational attainment (elementary or below) maintained significance across all adjusted models, while individuals with higher education levels (middle school or above) showed significance only in crude models, implying education might modulate the relationship between oral health and sarcopenia through its influence on health awareness and behavioral patterns. Additionally, associations observed in non-smokers and non-drinkers remained stable across all analytical models, indicating that good oral health may have a more direct and substantial independent effect on muscle function decline within populations already practicing healthier lifestyles. Moreover, regional subgroup analyses strongly supported the moderating role of eastern regions on the association, whereas central and western regions showed slightly attenuated effects. This further underscores that regional socioeconomic development and health resource allocation may interact significantly with oral health status and sarcopenia development. In summary, this study revealed a significant and heterogeneous association between edentulism and sarcopenia across demographic, socioeconomic, and metabolic subgroups, providing important scientific evidence for exploring potential biological mechanisms and socio-behavioral factors underlying the relationship between oral health and physical function decline in older populations. These findings not only emphasize the critical role of oral health in chronic disease management and healthy aging in the elderly but also provide a robust foundation for developing personalized public health policies and interventions. Through strengthened oral health maintenance and early interventions, we have the potential to slow sarcopenia progression among older adults, thereby improving overall health status and quality of life and promoting the strategic goal of healthy aging. From a clinical perspective, the findings of this study have clear practical implications, particularly by offering novel insights and guidance on the prevention, diagnosis, and management of edentulism and sarcopenia. Firstly, the significant association identified between edentulism and sarcopenia underscores the necessity of incorporating oral health assessment into comprehensive geriatric evaluations [22, 23]. Clinicians conducting geriatric assessments should specifically regard oral health status, especially tooth loss, as a key screening indicator for individuals at high risk of sarcopenia. Enhanced vigilance is particularly recommended for edentulous patients, who may benefit from more frequent monitoring of muscular function. This integrated assessment approach could facilitate early detection and timely interventions, thus reducing the incidence of sarcopenia-related complications. Secondly, the study provides a theoretical foundation for multidisciplinary collaborative interventions. Given the close relationship between edentulism and sarcopenia, establishing collaborative mechanisms among dental professionals, geriatricians, and nutritionists is recommended to develop targeted preventive and therapeutic strategies. For patients with edentulism, beyond traditional prosthodontic treatments, clinical care should also emphasize nutritional status, particularly protein and micronutrient intake, and provide nutritional counseling and supplementation when necessary. Additionally, encouraging participation in appropriate resistance training programs could help maintain or improve muscle mass and function. This multi-dimensional intervention strategy is expected to substantially enhance the overall health status and quality of life among edentulous individuals. Thirdly, the findings highlight the importance of oral health prevention in maintaining muscular function among older adults. Clinicians should strengthen oral health education among middle-aged populations, emphasizing the potential benefits of retaining natural teeth for reducing later-life sarcopenia risk [24-26]. For individuals already experiencing tooth loss, timely dental restoration to recover chewing functionality may help slow the rate of muscle function decline. Policymakers should particularly consider providing more accessible oral healthcare resources to populations with lower socioeconomic status as part of public health strategies aimed at preventing functional decline in older adults. Additionally, assessing denture use and chewing efficiency should be integrated into functional assessment protocols for older adults to provide comprehensive insights into the interrelationship between oral and muscular functions. Finally, the results suggest that clinicians should consider socioeconomic backgrounds and regional disparities when developing individualized intervention plans. More proactive oral health interventions and sarcopenia prevention strategies may be required for elderly populations with lower educational levels, residents in rural areas, and economically underdeveloped regions, thus mitigating health inequalities. At a policy-making level, integrating oral healthcare services into elderly functional maintenance programs could create a comprehensive health service model for older adults, thereby facilitating more holistic and effective elderly healthcare management [27, 28]. From a pathophysiological perspective, edentulism and sarcopenia may influence each other through multiple interconnected mechanisms, potentially forming a vicious cycle that exacerbates health risks in older populations. First, nutritional and metabolic imbalance pathway. Tooth loss severely limits older adults' intake of fiber-rich and high-protein foods, compelling a shift toward softer, carbohydrate-rich diets [29, 30]. Such dietary patterns frequently lead to inadequate intake of protein, vitamin D, and calcium, directly suppressing muscle protein synthesis and accelerating muscle breakdown. Several cohort studies among elderly individuals revealed that daily protein intake in edentulous participants was lower compared to dentate individuals, accompanied by significantly reduced serum albumin levels [31-33]. Hypoalbuminemia is recognized as a core risk factor for sarcopenia [34-36]. Second, chronic inflammation and oxidative stress pathway [13, 37, 38]. Long-term tooth loss often co-occurs with alveolar bone resorption and chronic oral infections, persistently releasing pro-inflammatory cytokines (e.g., IL-6, TNF-α) and reactive oxygen species (ROS) [39, 40]. These inflammatory mediators may induce muscle atrophy through activation of the ubiquitin-proteasome system (UPS) and inhibition of the mTOR signaling pathway[41, 42]. Cross-sectional data from the CHARLS indicated that edentulous individuals exhibited a 35% elevation in CRP levels compared to healthy controls. Third, functional limitation and behavioral changes. Loss of chewing function might decrease older adults' dietary intake willingness and social participation [43], further reducing physical activity levels. Muscle "disuse atrophy" compounded by sedentary behavior accelerates muscle loss [44-46]. Studies found that edentulous participants took fewer daily steps than controls, and individuals with low physical activity had a higher risk of developing sarcopenia [47-49]. Although the above mechanisms have been partially validated in Western populations, unique dietary structures, cultural habits, and genetic backgrounds among Asian populations, particularly Chinese older adults, might influence this relationship. For instance, the traditional Chinese diet primarily relies on grains with relatively limited protein sources, suggesting that the negative nutritional impact of edentulism might be even more pronounced. Additionally, limited accessibility to oral healthcare services in rural areas could exacerbate the synergistic deterioration associated with edentulism and sarcopenia. However, high-quality evidence specific to the Chinese population remains limited. This study has several notable strengths. Firstly, it utilized data from the large-scale national CHARLS cohort, encompassing middle-aged and older adults from 28 Chinese provinces, ensuring robust sample size and representativeness, thus enhancing the generalizability of the findings [50, 51]. Secondly, the study employed both cross-sectional and longitudinal analytical approaches, assessing not only the association but also the temporal relationship between edentulism and sarcopenia, thereby providing stronger evidence for causal inference [52, 53]. Thirdly, the use of diagnostic criteria established by the Asian Working Group for Sarcopenia (AWGS) ensures comparability of results internationally [54]. Fourthly, numerous potential confounders, including socio-demographic characteristics, lifestyle factors, regional differences, metabolic variables, and inflammatory markers, were carefully adjusted for, enhancing internal validity. Fifthly, sensitivity and subgroup analyses were conducted to verify the robustness of primary findings and explore heterogeneity in the association between edentulism and sarcopenia across different populations, providing scientific evidence for precision interventions. Nevertheless, several limitations should be acknowledged. Firstly, although sarcopenia was assessed according to AWGS criteria, muscle mass estimation was based on predictive equations rather than direct measurements (e.g., dual-energy X-ray absorptiometry or bioelectrical impedance analysis), potentially introducing measurement bias [3, 43]. Secondly, assessment of edentulism relied primarily on self-report and basic oral examination, lacking detailed oral health measures such as periodontal status and chewing efficiency, limiting deeper analysis of oral-muscle health interactions [55, 56]. Thirdly, despite controlling for numerous confounders, residual confounding could not be entirely excluded, particularly regarding psychosocial factors, detailed nutritional intake, and physical activity levels not comprehensively collected. Fourthly, the relatively short follow-up period (7 years) might insufficiently capture the long-term impact of exposure on outcomes. Fifthly, although missing data were handled using multiple imputation methods to reduce bias, residual inaccuracies might still affect results. Finally, as an observational study, the exact causal relationship between edentulism and sarcopenia cannot be established, nor can the possibility of bidirectional causality be ruled out [57-59]. Future research should adopt more precise measurement techniques for muscle mass and oral health, extend follow-up duration, incorporate more comprehensive confounding variables, and explore the mediating roles of nutritional status and inflammatory markers in the edentulism-sarcopenia association to further elucidate underlying biological mechanisms and causal pathways. 5. Conclusion In conclusion, this study highlights a significant and robust association between edentulism and sarcopenia in older Chinese adults. The findings underscore the importance of integrating oral health assessments into geriatric evaluations and emphasize multidisciplinary interventions involving oral health care, nutritional support, and exercise regimens to mitigate sarcopenia risk among edentulous individuals. Future research should employ precise measurement techniques, extend longitudinal follow-up periods, and include comprehensive confounding factors to better clarify the causative relationships and underlying biological mechanisms. Declarations 6 Author Contributions Zhai Tianyang : Data curation, Investigation, Funding acquisition, Project administration, Writing – original draft, Writing – review & editing. Sun ZhongYi : Formal Analysis, Software, Writing – review & editing. Xie QianYang : Validation, Visualization. Wu YanHui : Conceptualization, Writing – review & editing. Zou Huiru : Conceptualization, Methodology, Supervision, Resources, Project administration, Software, Writing – review & editing. Ni Jing : Conceptualization, Methodology, Supervision, Resources, Project administration, Software, Funding acquisition, Writing – review & editing.All authors read and approved the final manuscript. 7 Funding This study was supported by grants from ‘the Science and Technology Project of Songjiang District’ fund(22SJKJGG43), Cross-disciplinary Research Fund of Shanghai Ninth People's Hospital, Shanghai Jiao Tong university School of Medicine (JYJC202211), Teachers Practice Plan of Shanghai University(2022cxy-nj). We certify our research is free of conflict of interest. The authors do not have any financial interest in the companies whose materials are included in this article. 8 Acknowledgments We would like to extend our thanks to the CHARLS database teams for granting public access to their summary data. Furthermore, we are grateful to the principal investigators of the studies for their transparency in sharing their data for research purposes. 9 Conflict of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. 10 Ethics, Consent to Participate, and Consent to Publish declarations Not applicable. 11 Data Availability Statement The datasets generated and/or analysed during the current study are available in the CHARLS database (http://charls.pku.edu.cn/). References Al-Nasser L, Lamster IB: Prevention and management of periodontal diseases and dental caries in the older adults . Periodontol 2000 2020, 84 (1):69-83. Wu B, Luo H, Tan C, Qi X, Sloan FA, Kamer AR, Schwartz MD, Martinez M, Plassman BL: Diabetes, Edentulism, and Cognitive Decline: A 12-Year Prospective Analysis . Journal of dental research 2023, 102 (8):879-886. 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Tables Table 1 Variables Overall (n=17099) Sarcopenia P No(n=9853) Yes(n=2557) Edentulism(n,%) No 15478(91.2) 9259(94.0) 2005(78.5) <0.001 Yes 1494( 8.8) 588(6.0) 548(21.5) Age( years, median[IQR]) 58.0[51.0,65.0] 57.0[50.0,63.0] 67.0[62.0,74.0] <0.001 BMI( kg/m 2 , median[IQR]) 23.1[20.8,25.7] 24.3[22.3,26.6] 19.7[18.3,21.4] <0.001 Sex(n,%) Female 8747(51.2) 4397(44.6) 1825(71.4) <0.001 Male 8352(48.8) 5456(55.4) 732(28.6) Residence(n,%) Rural 10149(59.4) 5882(59.7) 1859(72.7) <0.001 Urban 6950(40.6) 3971(40.3) 698(27.3) Marital status(n,%) Married and living with a spouse 13676(80.1) 8427(85.5) 1769(69.2) <0.001 Married but living without a spouse 1177(6.9) 451(4.6) 70(2.7) Single, divorced, and windowed 2224(13.0) 975(9.9) 718(28.1) Education Status(n,%) Elementary school or below 11363(66.5) 6241(63.3) 2295(89.8) <0.001 Middle school or above 5730(33.5) 3612(36.7) 262(10.2) Smoking_Status(n,%) Non-smoker 10117(59.6) 5499(55.9) 1749(68.5) <0.001 Smoker 6845(40.4) 4347(44.1) 804 (31.5) Drinking Status(n,%) Drink but less than once a month 1335(8.5) 844(9.0) 140(5.8) <0.001 Drink more than once a month 3143(19.9) 2257(24.2) 294(12.2) Non-drinker 11306(71.6) 6233(66.8) 1982(82.0) Regional Category(n,%) East 6054(35.4) 3646(37.0) 704(27.5) <0.001 Midland 6203(36.3) 3575(36.3) 977(38.2) West 4835(28.3) 2630(26.7) 876(34.3) WC( cm, median[IQR]) 84.5[77.6,92.0] 87.4[81.0,94.0] 77.0[72.0,83.0] <0.001 TG( mg/dL, median[IQR]) 106.2[75.2,156.6] 109.7[77.0,163.7] 94.7[69.9,131.9] <0.001 HDL( mg/dL, median[IQR]) 49.1[39.9,59.9] 47.6[39.0,57.6] 55.7[45.6,66.5] <0.001 FBG( mg/dL, median[IQR]) 102.6[94.5,113.9] 103.1[95.2,115.2] 101.2[93.6,111.1] <0.001 SBP( mmHg, median[IQR]) 127.0[114.0,142.0] 127.0[115.0,142.0] 128.5[114.0,146.0] 0.053 DBP( mmHg [IQR]) 74.5[67.0,83.5] 76.0[68.0,84.5] 72.0[64.0,79.5] <0.001 CRP( mmol/L, [IQR]) 1.0[0.6,2.2] 1.1[0.6,2.2] 0.9[0.5,2.3] <0.001 ASMM( kg/m 2 , median[IQR]) 17.0[13.8,20.3] 18.5[15.5,21.2] 12.2[10.7,15.2] <0.001 HDL, high density lipoprotein; FBG, fasting blood glucose; SBP, systolic blood pressure; DBP, diastolic blood pressure; CRP, C reactive protein. Table 2 The results of cross-sectional analysis for Wave 1 data. Model Estimate SE Statistic P .value Non-PSM Model 1 1.359 0.059 23.122 <0.001 Model 2 0.219 0.093 2.363 0.018 Model 3 0.271 0.119 2.273 0.023 PSM Model 1 0.285 0.080 3.570 <0.001 Model 2 0.393 0.101 3.880 <0.001 Model 3 0.453 0.157 2.882 0.004 Model 1 represented the unadjusted crude association analysis; Model 2 adjusted for basic demographic characteristics including age, gender, urban-rural residence, education level, and marital status; Model 3 further adjusted for lifestyle factors (smoking, alcohol consumption), regional classification, and metabolic and inflammatory indicators (waist circumference, triglycerides, high-density lipoprotein, fasting blood glucose, systolic pressure, diastolic pressure, and C-reactive protein) based on Model 2. PSM, propensity score matching; SE, standard error. Table 3 The results of Longitudinal analysis for Wave 1-3 data. Model Estimate SE Statistic P .value Non-PSM Model 1 1.109 0.041 26.781 <0.001 Model 2 0.143 0.048 2.975 0.003 Model 3 0.070 0.057 1.225 0.221 PSM Model 1 0.217 0.056 3.860 <0.001 Model 2 0.171 0.060 2.866 0.004 Model 3 0.193 0.073 2.645 0.008 Model 1 represented the unadjusted crude association analysis; Model 2 adjusted for basic demographic characteristics including age, gender, urban-rural residence, education level, and marital status; Model 3 further adjusted for lifestyle factors (smoking, alcohol consumption), regional classification, and metabolic and inflammatory indicators (waist circumference, triglycerides, high-density lipoprotein, fasting blood glucose, systolic pressure, diastolic pressure, and C-reactive protein) based on Model 2. PSM, propensity score matching; SE, standard error. Additional Declarations No competing interests reported. Supplementary Files TableS1Subgroupanalysisincrosssectionalanalysis.xlsx TableS2Subgroupanalysisinlongitudinalanalysis.xlsx Cite Share Download PDF Status: Published Journal Publication published 02 Dec, 2025 Read the published version in BMC Oral Health → Version 1 posted Editorial decision: Revision requested 09 Sep, 2025 Reviews received at journal 07 Sep, 2025 Reviewers agreed at journal 04 Sep, 2025 Reviews received at journal 27 Aug, 2025 Reviewers agreed at journal 24 Aug, 2025 Reviewers agreed at journal 21 Aug, 2025 Reviewers invited by journal 30 May, 2025 Editor invited by journal 19 May, 2025 Editor assigned by journal 17 May, 2025 Submission checks completed at journal 17 May, 2025 First submitted to journal 10 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6637114","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":464450247,"identity":"ad190654-c709-489b-a9a5-c3834b1c3820","order_by":0,"name":"Zhai Tianyang","email":"","orcid":"","institution":"Sijing Hospital, Songjiang Stomatological Hospital, Shanghai Jiao Tong University School of Medicine;Prevention and Control Institute for Oral Diseases","correspondingAuthor":false,"prefix":"","firstName":"Zhai","middleName":"","lastName":"Tianyang","suffix":""},{"id":464450248,"identity":"85d76c5e-7ed1-4a52-8f1c-db72e175ff79","order_by":1,"name":"Sun ZhongYi","email":"","orcid":"","institution":"Sijing Hospital, Songjiang Stomatological Hospital, Shanghai Jiao Tong University School of Medicine;Prevention and Control Institute for Oral Diseases","correspondingAuthor":false,"prefix":"","firstName":"Sun","middleName":"","lastName":"ZhongYi","suffix":""},{"id":464450251,"identity":"642d4942-cc99-4728-b6e0-24be20b57d9f","order_by":2,"name":"Xie QianYang","email":"","orcid":"","institution":"Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, National Clinical Research Center for Oral Diseases, Shanghai Research Institute of Stomatology","correspondingAuthor":false,"prefix":"","firstName":"Xie","middleName":"","lastName":"QianYang","suffix":""},{"id":464450253,"identity":"7f763b1f-781c-4a68-bf48-b9da112b895a","order_by":3,"name":"Wu YanHui","email":"","orcid":"","institution":"Sijing Hospital, Songjiang Stomatological Hospital, Shanghai Jiao Tong University School of Medicine;Prevention and Control Institute for Oral Diseases","correspondingAuthor":false,"prefix":"","firstName":"Wu","middleName":"","lastName":"YanHui","suffix":""},{"id":464450254,"identity":"19927432-07c0-41c5-8b49-5686b70b93b9","order_by":4,"name":"Zou Huiru","email":"","orcid":"","institution":"Tianjin Stomatological Hospital, The Affiliated Stomatological Hospital of Nankai University","correspondingAuthor":false,"prefix":"","firstName":"Zou","middleName":"","lastName":"Huiru","suffix":""},{"id":464450257,"identity":"e2139083-cc9b-4d69-be5f-e554fd79188c","order_by":5,"name":"Ni Jing","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIie3RMUvDQBTA8Xc8uSwvdH1B8TM8CNgWiv0qVwJOHTp2kBoIOBVcHdTPkKnzlUImIWs2rTcLGTsImnZyMcnocP/llvfjuHsAPt9/7V2ABkFmoV7y5aB7HgGMwEW0Lox6fB3FUdqLAEykmguG98tZ3kWGQbmtzWJCYI/khVUOuP+oWsh4nSAbuSGVFgv1vGEcgo7jeQsRm0BDdoQqy+Fzw3qckj5vJaXDg5Fv0ggC4ROT2C5SJbq5xRLpM1FhytyDuKuRkYSYdPPJBUuUdb2lnLmq/rqeTt9cs8rb1d1DkO1dG/ldcDgd2HPc5/P5fH/3AzsERyzaO+ErAAAAAElFTkSuQmCC","orcid":"","institution":"Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, National Clinical Research Center for Oral Diseases, Shanghai Research Institute of Stomatology","correspondingAuthor":true,"prefix":"","firstName":"Ni","middleName":"","lastName":"Jing","suffix":""}],"badges":[],"createdAt":"2025-05-11 01:23:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6637114/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6637114/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12903-025-07430-z","type":"published","date":"2025-12-02T15:57:18+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":83817275,"identity":"cfe2a4f7-7a94-444e-945b-36164779343c","added_by":"auto","created_at":"2025-06-03 07:54:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":168188,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of the association between edentulism and sarcopenia across different subgroups in the cross-sectional analysis. This figure illustrates the odds ratios (ORs) and 95% confidence intervals (CIs) for the association between edentulism and sarcopenia across sex, residence, marital status, education level, smoking status, drinking status, and regional categories, based on Model 1 (crude model), Model 2 (adjusted for demographic factors), and Model 3 (further adjusted for metabolic indicators).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6637114/v1/526e60b388daf49d99c4a9c2.png"},{"id":97723797,"identity":"f9b78370-d5d1-4956-b5d8-392278650558","added_by":"auto","created_at":"2025-12-08 16:06:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4285830,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6637114/v1/09ac5785-c6e1-47da-8fd7-e551d87e988f.pdf"},{"id":83817272,"identity":"f96a7d5d-9def-4cbb-83ee-54020c3ed8ef","added_by":"auto","created_at":"2025-06-03 07:54:11","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":16241,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1Subgroupanalysisincrosssectionalanalysis.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6637114/v1/4b8d2644ea03706457ddb98b.xlsx"},{"id":83817792,"identity":"8b5142f5-93e7-45ed-9be4-703a5f116400","added_by":"auto","created_at":"2025-06-03 08:02:11","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":61103,"visible":true,"origin":"","legend":"","description":"","filename":"TableS2Subgroupanalysisinlongitudinalanalysis.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6637114/v1/4559f045537f89b163992730.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Edentulism as an Independent Risk Factor for Sarcopenia: Evidence from Cross-sectional and Longitudinal Analyses Based on the CHARLS Cohort","fulltext":[{"header":"1 Background","content":"\u003cp\u003eWith the acceleration of global population aging, China has become one of the countries with the largest elderly population and fastest aging rate. According to the \"China Aging Career Development Report (2024),\" China's population aged 60 and above has reached 280\u0026nbsp;million, accounting for over 20% of the total population. Against this backdrop, age-related chronic diseases and functional decline issues have become increasingly prominent. Among them, edentulism and sarcopenia, two geriatric syndromes with high prevalence but often overlooked, are seriously affecting the quality of life and healthy life expectancy of older adults[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Edentulism (complete tooth loss) is prevalent among older Chinese adults. National oral health epidemiological survey data show that the prevalence of edentulism among adults aged 65\u0026ndash;74 years reaches 8.7%, with rates exceeding 12% in rural areas [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Tooth loss not only directly leads to decreased masticatory function but may also indirectly increase the risk of various systemic diseases by limiting dietary choices, inducing malnutrition, and creating chronic inflammatory states [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Meanwhile, sarcopenia (characterized by progressive decline in muscle mass, strength, and function) has a prevalence of approximately 10%-15% among community-dwelling older adults and is significantly associated with falls, fractures, functional disability, and mortality risk [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Studies indicate that all-cause mortality rates within five years are 1.5\u0026ndash;2.3 times higher in sarcopenia patients compared to healthy populations [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], with disease burden exceeding that of traditional chronic conditions such as hypertension and diabetes. In recent years, although research has begun to focus on the relationship between oral health and muscle function, these studies have notable limitations, such as insufficient sample representativeness [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. As a country with deep aging trends and significant regional differences, China urgently needs empirical research with national representativeness. Furthermore, existing research designs are predominantly cross-sectional, unable to establish causal relationships between edentulism and sarcopenia, and inadequately control for potential confounding factors such as socioeconomic status and comorbidities. Notably, although both edentulism and sarcopenia are closely related to aging, the potential associative mechanisms between them have not been systematically explored.\u003c/p\u003e \u003cp\u003eAddressing the evidence gap in research on the association between edentulism and sarcopenia among Chinese older adults, this study integrates multiple waves of longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS) from 2011\u0026ndash;2020[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Through cross-sectional analysis, we reveal the prevalence association between edentulism and sarcopenia and its differential patterns across urban-rural, gender, and regional dimensions. Based on the 2011 baseline population without sarcopenia, we conduct a 7-year follow-up to assess the long-term impact of edentulism on sarcopenia incidence risk. The research findings will promote the inclusion of oral health indicators in comprehensive geriatric assessment systems, drive the development of evidence-based nutritional intervention strategies, and provide theoretical foundations for establishing an integrated \"oral-muscular\" health management framework, thereby effectively addressing major public health challenges brought by population aging.\u003c/p\u003e"},{"header":"2 Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Research Design and Data Source\u003c/h2\u003e \u003cp\u003eThis study employs an observational cohort design based on publicly available data from the CHARLS database. As a national cohort study covering 28 provinces in China, CHARLS systematically tracks changes in health, socioeconomic, and behavioral characteristics of middle-aged and older adults aged 45 and above. The project completed baseline survey (Wave 1) in 2011, with subsequent follow-ups every 2\u0026ndash;3 years (2013, 2015, 2018, and 2020), comprehensively collecting multidimensional information including participants' demographic characteristics, health status, biomarkers (including blood tests), and functional assessments [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. This research design integrates both cross-sectional and longitudinal analytical methods: the cross-sectional component evaluates the prevalence association patterns between edentulism and sarcopenia, while the longitudinal component follows individuals without sarcopenia at the 2011 baseline to track their risk of developing sarcopenia through 2018, thereby exploring the temporal relationship and potential mechanisms between these two geriatric syndromes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Study Population and Sample Selection\u003c/h2\u003e \u003cp\u003eInclusion criteria: (1) age\u0026thinsp;\u0026ge;\u0026thinsp;45 years; (2) complete oral examination records (for defining edentulism); (3) available muscle mass and strength measurement data (for diagnosing sarcopenia); (4) complete sociodemographic, health behavior, and comorbidity information at baseline (2011) and at least one follow-up. Exclusion criteria: (1) diagnosed with sarcopenia at baseline (for longitudinal analysis only); (2) missing key variables (such as grip strength, walking speed, number of teeth); (3) non-fasting status during blood sample collection. The final samples were used for cross-sectional and longitudinal analyses, ensuring adequate representativeness.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Variable Definitions and Measurements\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1 Primary Exposure: Edentulism\u003c/h2\u003e \u003cp\u003eEdentulism was defined as having no natural teeth remaining in the oral cavity (complete tooth loss), assessed and confirmed through oral examination records from the CHARLS project. At baseline survey (Wave 1), variables wearing_dentures and fixed_or_removable were used to determine whether respondents wore dentures and the type of dentures; in subsequent follow-ups (Wave 2 to Wave 4), complete tooth loss was directly assessed. Based on these evaluations, edentulism status was set as a binary variable, where \"0\" indicated having teeth (partial or complete) and \"1\" indicated edentulism (complete tooth loss).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2 Outcome Variable: Sarcopenia\u003c/h2\u003e \u003cp\u003eThis study assessed sarcopenia status according to the Asian Working Group for Sarcopenia (AWGS) standards, defined and calculated through the following steps[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]:\u003c/p\u003e \u003cp\u003e①. Muscle mass assessment: Appendicular skeletal muscle mass index (ASM) was calculated based on gender-specific formulas:\u003c/p\u003e \u003cp\u003eASM\u0026thinsp;=\u0026thinsp;0.193 \u0026times; weight(kg)\u0026thinsp;+\u0026thinsp;0.107 \u0026times; height(cm) \u0026minus;\u0026thinsp;4.157 \u0026times; sex(male\u0026thinsp;=\u0026thinsp;1; female\u0026thinsp;=\u0026thinsp;2) \u0026minus;\u0026thinsp;0.037 \u0026times; age(years) \u0026minus;\u0026thinsp;2.631.\u003c/p\u003e \u003cp\u003eASM_Ht2\u0026thinsp;=\u0026thinsp;ASM / (height\u0026sup2;) (height in meters)\u003c/p\u003e \u003cp\u003eLow muscle mass was defined as ASM/Ht\u0026sup2; \u0026lt; 6.88 kg/m\u0026sup2; for men or ASM/Ht\u0026sup2; \u0026lt; 5.69 kg/m\u0026sup2; for women.\u003c/p\u003e \u003cp\u003e②. Muscle strength assessment: Grip strength level was determined by calculating the average of left and right hand grip strength measurements. Low grip strength was defined as \u0026lt;\u0026thinsp;28 kg for men or \u0026lt;\u0026thinsp;18 kg for women.\u003c/p\u003e \u003cp\u003e③. Physical function assessment: Determination was based on chair stand time and walking speed test. Physical function impairment was defined as \u0026gt;\u0026thinsp;12 seconds for five repeated chair stands or walking speed\u0026thinsp;\u0026lt;\u0026thinsp;1 m/s.\u003c/p\u003e \u003cp\u003e④. Sarcopenia diagnosis criteria: Sarcopenia was diagnosed when low muscle mass occurred concurrently with either low grip strength or physical function impairment.\u003c/p\u003e \u003cp\u003eThis diagnostic method complies with the AWGS standard definition of sarcopenia, ensuring comparability with international sarcopenia research and clinical relevance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.3.3 Covariates and Confounding Factors\u003c/h2\u003e \u003cp\u003eThis study comprehensively considered multiple potential confounding factors that might influence the association between edentulism and sarcopenia. For demographic variables, we included age, gender, residence type, marital status, and education level. Lifestyle factors included smoking status and alcohol consumption. Considering China's regional development disparities, we categorized participants into \"Eastern,\" \"Midland,\" and \"Western\" geographic regions based on regional variables. Additionally, health and metabolic indicators encompassed body mass index, waist circumference, triglycerides, high-density lipoprotein cholesterol, fasting blood glucose, blood pressure, and the inflammatory marker C-reactive protein, to comprehensively control for potential effects of metabolic and inflammatory status on the studied association.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical Analysis\u003c/h2\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.4.1 Cross-sectional Analysis\u003c/h2\u003e \u003cp\u003eThis study first conducted descriptive statistical analysis, dividing the sample into two groups based on edentulism status. Continuous variables were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median (interquartile range), while categorical variables were presented as frequency (percentage). Between-group differences were evaluated using t-tests (for normally distributed continuous variables), Mann-Whitney U tests (for non-normally distributed continuous variables), or chi-square tests (for categorical variables), according to data distribution characteristics. In multivariate analysis, we constructed three progressively adjusted logistic regression models with sarcopenia (binary: yes/no) as the dependent variable and edentulism as the independent variable. Model 1 represented the unadjusted crude association analysis; Model 2 adjusted for basic demographic characteristics including age, gender, urban-rural residence, education level, and marital status; Model 3 further adjusted for lifestyle factors (smoking, alcohol consumption), regional classification, and metabolic and inflammatory indicators (waist circumference, triglycerides, high-density lipoprotein, fasting blood glucose, systolic pressure, diastolic pressure, and C-reactive protein) based on Model 2. All analytical results were presented as odds ratios (OR) with their 95% confidence intervals (CI) to assess the strength and direction of the cross-sectional association between edentulism and sarcopenia.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.4.2 Longitudinal Analysis\u003c/h2\u003e \u003cp\u003eTo explore the temporal relationship between edentulism and sarcopenia occurrence, Cox proportional hazards regression models were employed for longitudinal analysis. Using the baseline population without sarcopenia as the study cohort, follow-up time was defined as the number of years from baseline to event occurrence or observation endpoint, with the four survey waves corresponding to observation time points of 0, 2, 4, and 7 years. The outcome event was defined as new-onset sarcopenia (final_event\u0026thinsp;=\u0026thinsp;1 indicating diagnosis of sarcopenia during any follow-up wave), with event time (final_time) recorded as the follow-up time point of first sarcopenia diagnosis; for participants without sarcopenia during follow-up, the time point of the last follow-up was recorded and treated as censored. The Cox model adjusted for the same variables as Model 3 in the cross-sectional analysis, with results presented as hazard ratios (HR) with their 95% confidence intervals. Additionally, we conducted two sensitivity analyses: first, excluding individuals with specific health issues at baseline to assess result robustness; second, using multiple imputation methods for variables with missing rates below 5% to reduce information bias.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e2.4.3 Sensitivity Analysis\u003c/h2\u003e \u003cp\u003eIn this study, propensity score matching (PSM) was performed using age, sex, residence, marital status, educational attainment, smoking status, drinking status, and regional category as covariates [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. A 1:1 nearest neighbor matching method was applied to minimize confounding bias [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The matched data were subsequently analyzed using logistic regression and Cox proportional hazards models to evaluate the association between edentulism and the outcome variable, sarcopenia.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e2.4.4 Subgroup Analysis\u003c/h2\u003e \u003cp\u003eConsidering that population heterogeneity might affect the generalizability of research findings, this study conducted subgroup analyses for key demographic and lifestyle characteristics, including gender (male/female), residence type (urban/rural), marital status (married cohabiting/married separated/single), education level (primary school and below/middle school and above), smoking status (smoker/non-smoker), alcohol consumption status (non-drinker/light drinker/regular drinker), and regional classification (eastern/central/western). By incorporating interaction terms and evaluating their statistical significance, we explored differential patterns of association between edentulism and sarcopenia across different population characteristic strata. All statistical analyses were performed using R 4.3.3 and related statistical packages, with two-sided tests and significance level set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e \u003cp\u003e\u003cstrong\u003e2.5 Ethical Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe CHARLS study was approved by the Biomedical Ethics Committee of Peking University, and all participants signed written informed consent. This study uses publicly available anonymized data, which is exempt from ethical review.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Baseline Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 17,099 participants were included in the baseline analysis (Table 1). Among them, 1,494 individuals were diagnosed with edentulism, accounting for 8.8% of the total sample, and 2,557 individuals were identified with sarcopenia, with a prevalence of 15.0%. Notably, the prevalence of sarcopenia was significantly higher among participants with edentulism (36.7%, 548/1494) compared to those without edentulism (12.9%, 2005/15478). Additionally, the prevalence of edentulism was significantly higher in individuals with sarcopenia than in those without (P \u0026lt; 0.001), suggesting a potential association between the two conditions.\u003c/p\u003e\n\u003cp\u003eRegarding demographic characteristics, participants with sarcopenia were significantly older than those without (67.0 vs. 57.0 years, P \u0026lt; 0.001) and were more likely to reside in rural areas (72.7% vs. 59.7%, P \u0026lt; 0.001). Marital status also differed significantly between groups, with a higher proportion of single, divorced, or widowed individuals in the sarcopenia group (28.1% vs. 9.9%, P \u0026lt; 0.001). Educational attainment was lower in the sarcopenia group, with 89.8% having only elementary school education or below, compared to 63.3% in the non-sarcopenia group (P \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003eIn terms of lifestyle factors, a higher proportion of participants in the sarcopenia group were non-smokers (68.5% vs. 55.9%, P \u0026lt; 0.001) and non-drinkers (82.0% vs. 66.8%, P \u0026lt; 0.001). Regionally, individuals with sarcopenia were more frequently from western regions (34.3% vs. 26.7%, P \u0026lt; 0.001). Metabolic and health-related indicators also differed significantly. Participants with sarcopenia had significantly lower BMI (19.7 vs. 24.3, P \u0026lt; 0.001), waist circumference (77.0 cm vs. 87.4 cm, P \u0026lt; 0.001), and triglyceride levels (94.7 vs. 109.7, P \u0026lt; 0.001), but higher HDL-C levels (55.7 vs. 47.6, P \u0026lt; 0.001). Systolic blood pressure was slightly higher in the sarcopenia group but did not reach statistical significance (128.5 vs. 127.0 mmHg, P = 0.053), whereas diastolic blood pressure was significantly lower (72.0 vs. 76.0 mmHg, P \u0026lt; 0.001). Interestingly, CRP levels were lower in the sarcopenia group compared to the non-sarcopenia group (0.9 vs. 1.1, P \u0026lt; 0.001), and fasting blood glucose levels were also significantly reduced (101.2 vs. 103.1 mg/dL, P \u0026lt; 0.001). In summary, these findings suggest a potential link between edentulism and sarcopenia, and reveal a distinct profile of socio-demographic and metabolic characteristics among individuals with sarcopenia, including older age, lower socioeconomic status, rural residence, and specific metabolic traits.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Cross-sectional Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the cross-sectional analysis based on wave 1 data, a significant association was observed between edentulism and sarcopenia (Table 2). In the crude model (Model 1), individuals with edentulism had a significantly increased risk of sarcopenia compared to those without (β = 1.359, P \u0026lt; 0.001). After adjustment for demographic confounders (Model 2), the association remained statistically significant, though attenuated (β = 0.219, P = 0.018). Following further adjustment for metabolic variables—including waist circumference, triglycerides, HDL cholesterol, fasting glucose, blood pressure—and C-reactive protein levels (Model 3), the association persisted (β = 0.271, P = 0.023).\u003c/p\u003e\n\u003cp\u003eIn the PSM population, edentulism remained significantly associated with an increased risk of sarcopenia. In the crude PSM model (Model 1), the association was evident (β = 0.285, P \u0026lt; 0.001). After adjusting for demographic variables (Model 2), the effect size increased (β = 0.393, P \u0026lt; 0.001), and further adjustment for metabolic, blood pressure, and inflammatory indicators (Model 3) yielded a consistently stronger association (β = 0.453, P = 0.004), indicating a robust and progressive link between edentulism and sarcopenia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Longitudinal Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the longitudinal analysis across waves 1 to 3, a significant association was observed between edentulism and the risk of sarcopenia (Table 3). In the crude model (Model 1), edentulous individuals had a significantly higher risk of developing sarcopenia compared to those without edentulism (β = 1.109, P \u0026lt; 0.001). After adjusting for demographic covariates (Model 2), the association was attenuated but remained statistically significant (β = 0.143, P = 0.003). However, further adjustment for metabolic variables, including waist circumference, triglycerides, HDL cholesterol, fasting glucose, blood pressure, and C-reactive protein (Model 3), rendered the association non-significant (β = 0.070, P = 0.221).\u003c/p\u003e\n\u003cp\u003eFollowing PSM, the association remained robust. Edentulism was still positively associated with sarcopenia risk in the crude PSM model (β = 0.217, P \u0026lt; 0.001), and this association persisted after adjusting for demographic (Model 2, β = 0.171, P = 0.004) and metabolic variables (Model 3, β = 0.193, P = 0.008), suggesting a stable and independent relationship.\u003c/p\u003e\n\u003cp\u003eIn the cross-sectional subgroup analysis, the association between edentulism and sarcopenia was generally consistent across different demographic groups, with some degree of heterogeneity (Figure 1). When stratified by sex, edentulism was associated with an increased risk of sarcopenia in both males and females, with a slightly stronger effect observed among males. Stratified by residence, the association remained significant among both rural and urban populations, but was more pronounced in rural residents. In marital status subgroups, the association weakened slightly among single, divorced, or widowed individuals compared to those married and living with a spouse, yet a positive trend was still observed. Stratification by education level revealed that individuals with elementary education or below exhibited a stronger association. Regarding smoking and drinking status, the association was more evident among non-smokers and non-drinkers. Regional analysis showed the most prominent association in western regions, with positive associations also observed in the midland and eastern regions.Overall, these findings suggest that edentulism is a robust risk factor for sarcopenia across various subgroups, although differences exist by sex, residence, education level, and lifestyle factors, highlighting the need for tailored intervention strategies. Detailed information for these results are provided in Table S1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5 Wave 1-3 Longitudinal Subgroup Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAcross progressively adjusted models, the positive association between edentulism and sarcopenia remained statistically significant in many subgroups, although attenuation of effect sizes was observed in Model 2 and Model 3 (Table S2): In the sex-stratified analysis, both men and women showed significant associations in Model 1. In women, the effect size slightly decreased across models but remained significant. In men, the association remained strong and significant even in Model 3. In residential subgroups, both urban and rural populations demonstrated significant associations in Model 1 and Model 2. The effect weakened in urban populations in Model 3 but remained statistically significant in rural groups. Marital status subgroups showed significant associations in “married cohabiting” and “married living separately” in Model 1 and 2. In Model 3, only the ‘married cohabiting’ subgroup retained statistical significance, possibly due to reduced statistical power or confounding in other groups. For educational level, individuals with elementary education or below maintained consistent significance across all models, while those with middle school or higher education only showed significance in Model 1, losing it in later models. In smoking and drinking subgroups, Model 1 revealed strong associations across all categories. Model 2 and 3 showed more stable associations in non-smokers and non-drinkers, suggesting potential behavioral effect modification. Regional analysis demonstrated that in Model 1, Eastern, Central, and Western regions all had significant associations. In Model 2 and Model 3, the Eastern region retained the strongest and most stable effect, while significance in other regions diminished. Overall, even after adjusting for demographic, metabolic, and inflammatory confounders, edentulism remained a robust and independent risk factor for sarcopenia across diverse population strata.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn this study, we utilized cross-sectional analysis, longitudinal cohort follow-up, and PSM methods to uncover a significant association between edentulism and sarcopenia, and further investigated the heterogeneity of this relationship across different demographic and metabolic subgroups. Our findings revealed that among 17,099 participants included in this analysis, the overall prevalence of edentulism was 8.8%, while sarcopenia prevalence reached 15.0%. Notably, the prevalence of edentulism was significantly higher among individuals with sarcopenia compared to those without. Both cross-sectional and longitudinal analyses consistently showed robust positive associations between edentulism and sarcopenia risk, and these associations remained significant across most models even after adjusting for various potential confounders, including demographic characteristics, metabolic indicators, and inflammatory markers. These results provide strong evidence for further exploring the biological mechanisms and public health intervention strategies linking oral health and muscle function decline. Results from crude to progressively adjusted models indicated some attenuation of the association between edentulism and sarcopenia; however, analyses following PSM adjustment conversely demonstrated a gradually strengthened relationship. This effect reached its peak in the cross-sectional analysis in Model 3. Similarly, in the longitudinal analysis following PSM adjustment, the association remained robust and independent. Subgroup analyses further highlighted that the risk effect of edentulism on sarcopenia was more pronounced among males, residents of western regions, individuals with elementary education or below, non-smokers, and non-drinkers. Although slightly weaker in single, divorced, or widowed individuals, the overall positive trend remained consistent. These findings suggest that the impact of edentulism on sarcopenia risk could be modified by socioeconomic status, lifestyle habits, and regional factors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo further clarify the stability of the association between edentulism and sarcopenia and potential confounding factors, we conducted longitudinal subgroup analyses. Results indicated a stronger and more consistent association effect among males compared to females across all models. Analyses by urban and rural residence demonstrated that the association in rural residents was consistently stronger and sustained across models compared to urban residents. Notably, participants with lower educational attainment (elementary or below) maintained significance across all adjusted models, while individuals with higher education levels (middle school or above) showed significance only in crude models, implying education might modulate the relationship between oral health and sarcopenia through its influence on health awareness and behavioral patterns. Additionally, associations observed in non-smokers and non-drinkers remained stable across all analytical models, indicating that good oral health may have a more direct and substantial independent effect on muscle function decline within populations already practicing healthier lifestyles. Moreover, regional subgroup analyses strongly supported the moderating role of eastern regions on the association, whereas central and western regions showed slightly attenuated effects. This further underscores that regional socioeconomic development and health resource allocation may interact significantly with oral health status and sarcopenia development. In summary, this study revealed a significant and heterogeneous association between edentulism and sarcopenia across demographic, socioeconomic, and metabolic subgroups, providing important scientific evidence for exploring potential biological mechanisms and socio-behavioral factors underlying the relationship between oral health and physical function decline in older populations. These findings not only emphasize the critical role of oral health in chronic disease management and healthy aging in the elderly but also provide a robust foundation for developing personalized public health policies and interventions. Through strengthened oral health maintenance and early interventions, we have the potential to slow sarcopenia progression among older adults, thereby improving overall health status and quality of life and promoting the strategic goal of healthy aging.\u003c/p\u003e\n\u003cp\u003eFrom a clinical perspective, the findings of this study have clear practical implications, particularly by offering novel insights and guidance on the prevention, diagnosis, and management of edentulism and sarcopenia. Firstly, the significant association identified between edentulism and sarcopenia underscores the necessity of incorporating oral health assessment into comprehensive geriatric evaluations [22, 23]. Clinicians conducting geriatric assessments should specifically regard oral health status, especially tooth loss, as a key screening indicator for individuals at high risk of sarcopenia. Enhanced vigilance is particularly recommended for edentulous patients, who may benefit from more frequent monitoring of muscular function. This integrated assessment approach could facilitate early detection and timely interventions, thus reducing the incidence of sarcopenia-related complications.\u003c/p\u003e\n\u003cp\u003eSecondly, the study provides a theoretical foundation for multidisciplinary collaborative interventions. Given the close relationship between edentulism and sarcopenia, establishing collaborative mechanisms among dental professionals, geriatricians, and nutritionists is recommended to develop targeted preventive and therapeutic strategies. For patients with edentulism, beyond traditional prosthodontic treatments, clinical care should also emphasize nutritional status, particularly protein and micronutrient intake, and provide nutritional counseling and supplementation when necessary. Additionally, encouraging participation in appropriate resistance training programs could help maintain or improve muscle mass and function. This multi-dimensional intervention strategy is expected to substantially enhance the overall health status and quality of life among edentulous individuals.\u003c/p\u003e\n\u003cp\u003eThirdly, the findings highlight the importance of oral health prevention in maintaining muscular function among older adults. Clinicians should strengthen oral health education among middle-aged populations, emphasizing the potential benefits of retaining natural teeth for reducing later-life sarcopenia risk [24-26]. For individuals already experiencing tooth loss, timely dental restoration to recover chewing functionality may help slow the rate of muscle function decline. Policymakers should particularly consider providing more accessible oral healthcare resources to populations with lower socioeconomic status as part of public health strategies aimed at preventing functional decline in older adults. Additionally, assessing denture use and chewing efficiency should be integrated into functional assessment protocols for older adults to provide comprehensive insights into the interrelationship between oral and muscular functions.\u003c/p\u003e\n\u003cp\u003eFinally, the results suggest that clinicians should consider socioeconomic backgrounds and regional disparities when developing individualized intervention plans. More proactive oral health interventions and sarcopenia prevention strategies may be required for elderly populations with lower educational levels, residents in rural areas, and economically underdeveloped regions, thus mitigating health inequalities. At a policy-making level, integrating oral healthcare services into elderly functional maintenance programs could create a comprehensive health service model for older adults, thereby facilitating more holistic and effective elderly healthcare management [27, 28].\u003c/p\u003e\n\u003cp\u003eFrom a pathophysiological perspective, edentulism and sarcopenia may influence each other through multiple interconnected mechanisms, potentially forming a vicious cycle that exacerbates health risks in older populations. First, nutritional and metabolic imbalance pathway. Tooth loss severely limits older adults' intake of fiber-rich and high-protein foods, compelling a shift toward softer, carbohydrate-rich diets [29, 30]. Such dietary patterns frequently lead to inadequate intake of protein, vitamin D, and calcium, directly suppressing muscle protein synthesis and accelerating muscle breakdown. Several cohort studies among elderly individuals revealed that daily protein intake in edentulous participants was lower compared to dentate individuals, accompanied by significantly reduced serum albumin levels [31-33]. Hypoalbuminemia is recognized as a core risk factor for sarcopenia [34-36].\u003c/p\u003e\n\u003cp\u003eSecond, chronic inflammation and oxidative stress pathway [13, 37, 38]. Long-term tooth loss often co-occurs with alveolar bone resorption and chronic oral infections, persistently releasing pro-inflammatory cytokines (e.g., IL-6, TNF-α) and reactive oxygen species (ROS) [39, 40]. These inflammatory mediators may induce muscle atrophy through activation of the ubiquitin-proteasome system (UPS) and inhibition of the mTOR signaling pathway[41, 42]. Cross-sectional data from the CHARLS indicated that edentulous individuals exhibited a 35% elevation in CRP levels compared to healthy controls.\u003c/p\u003e\n\u003cp\u003eThird, functional limitation and behavioral changes. Loss of chewing function might decrease older adults' dietary intake willingness and social participation [43], further reducing physical activity levels. Muscle \"disuse atrophy\" compounded by sedentary behavior accelerates muscle loss [44-46]. Studies found that edentulous participants took fewer daily steps than controls, and individuals with low physical activity had a higher risk of developing sarcopenia [47-49].\u003c/p\u003e\n\u003cp\u003eAlthough the above mechanisms have been partially validated in Western populations, unique dietary structures, cultural habits, and genetic backgrounds among Asian populations, particularly Chinese older adults, might influence this relationship. For instance, the traditional Chinese diet primarily relies on grains with relatively limited protein sources, suggesting that the negative nutritional impact of edentulism might be even more pronounced. Additionally, limited accessibility to oral healthcare services in rural areas could exacerbate the synergistic deterioration associated with edentulism and sarcopenia. However, high-quality evidence specific to the Chinese population remains limited.\u003c/p\u003e\n\u003cp\u003eThis study has several notable strengths. Firstly, it utilized data from the large-scale national CHARLS cohort, encompassing middle-aged and older adults from 28 Chinese provinces, ensuring robust sample size and representativeness, thus enhancing the generalizability of the findings [50, 51]. Secondly, the study employed both cross-sectional and longitudinal analytical approaches, assessing not only the association but also the temporal relationship between edentulism and sarcopenia, thereby providing stronger evidence for causal inference [52, 53]. Thirdly, the use of diagnostic criteria established by the Asian Working Group for Sarcopenia (AWGS) ensures comparability of results internationally [54]. Fourthly, numerous potential confounders, including socio-demographic characteristics, lifestyle factors, regional differences, metabolic variables, and inflammatory markers, were carefully adjusted for, enhancing internal validity. Fifthly, sensitivity and subgroup analyses were conducted to verify the robustness of primary findings and explore heterogeneity in the association between edentulism and sarcopenia across different populations, providing scientific evidence for precision interventions.\u003c/p\u003e\n\u003cp\u003eNevertheless, several limitations should be acknowledged. Firstly, although sarcopenia was assessed according to AWGS criteria, muscle mass estimation was based on predictive equations rather than direct measurements (e.g., dual-energy X-ray absorptiometry or bioelectrical impedance analysis), potentially introducing measurement bias [3, 43]. Secondly, assessment of edentulism relied primarily on self-report and basic oral examination, lacking detailed oral health measures such as periodontal status and chewing efficiency, limiting deeper analysis of oral-muscle health interactions [55, 56]. Thirdly, despite controlling for numerous confounders, residual confounding could not be entirely excluded, particularly regarding psychosocial factors, detailed nutritional intake, and physical activity levels not comprehensively collected. Fourthly, the relatively short follow-up period (7 years) might insufficiently capture the long-term impact of exposure on outcomes. Fifthly, although missing data were handled using multiple imputation methods to reduce bias, residual inaccuracies might still affect results. Finally, as an observational study, the exact causal relationship between edentulism and sarcopenia cannot be established, nor can the possibility of bidirectional causality be ruled out [57-59]. Future research should adopt more precise measurement techniques for muscle mass and oral health, extend follow-up duration, incorporate more comprehensive confounding variables, and explore the mediating roles of nutritional status and inflammatory markers in the edentulism-sarcopenia association to further elucidate underlying biological mechanisms and causal pathways.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, this study highlights a significant and robust association between edentulism and sarcopenia in older Chinese adults. The findings underscore the importance of integrating oral health assessments into geriatric evaluations and emphasize multidisciplinary interventions involving oral health care, nutritional support, and exercise regimens to mitigate sarcopenia risk among edentulous individuals. Future research should employ precise measurement techniques, extend longitudinal follow-up periods, and include comprehensive confounding factors to better clarify the causative relationships and underlying biological mechanisms.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e6 Author Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eZhai Tianyang\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Data curation, Investigation, Funding acquisition, Project administration, Writing – original draft, Writing – review \u0026amp; editing.\u0026nbsp;\u003cstrong\u003eSun ZhongYi\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Formal Analysis, Software, Writing – review \u0026amp; editing.\u0026nbsp;\u003cstrong\u003eXie QianYang\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003eValidation, Visualization.\u0026nbsp;\u003cstrong\u003eWu YanHui\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Conceptualization, Writing – review \u0026amp; editing.\u0026nbsp;\u003cstrong\u003eZou Huiru\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Conceptualization, Methodology, Supervision, Resources, Project administration, Software, Writing – review \u0026amp; editing.\u0026nbsp;\u003cstrong\u003eNi Jing\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Conceptualization, Methodology, Supervision, Resources, Project administration, Software, Funding acquisition, Writing – review \u0026amp; editing.All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e7 Funding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by grants from ‘the Science and Technology Project of Songjiang District’ fund(22SJKJGG43), Cross-disciplinary Research Fund of Shanghai Ninth People's Hospital, Shanghai Jiao Tong university School of Medicine (JYJC202211), Teachers Practice Plan of Shanghai University(2022cxy-nj). We certify our research is free of conflict of interest. The authors do not have any financial interest in the companies whose materials are included in this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e8 Acknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to extend our thanks to the CHARLS database teams for granting public access to their summary data. Furthermore, we are grateful to the principal investigators of the studies for their transparency in sharing their data for research purposes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e9 Conflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e10\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eEthics, Consent to Participate, and Consent to Publish declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e11 Data Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are available in the CHARLS database (http://charls.pku.edu.cn/).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAl-Nasser L, Lamster IB: \u003cstrong\u003ePrevention and management of periodontal diseases and dental caries in the older adults\u003c/strong\u003e. \u003cem\u003ePeriodontol 2000 \u003c/em\u003e2020, \u003cstrong\u003e84\u003c/strong\u003e(1):69-83.\u003c/li\u003e\n\u003cli\u003eWu B, Luo H, Tan C, Qi X, Sloan FA, Kamer AR, Schwartz MD, Martinez M, Plassman BL: \u003cstrong\u003eDiabetes, Edentulism, and Cognitive Decline: A 12-Year Prospective Analysis\u003c/strong\u003e. \u003cem\u003eJournal of dental research \u003c/em\u003e2023, \u003cstrong\u003e102\u003c/strong\u003e(8):879-886.\u003c/li\u003e\n\u003cli\u003eAn TJ, Lim J, Lee H, Ji S, Jung HW, Baek JY, Lee E, Jang IY: \u003cstrong\u003eBreathlessness, Frailty, and Sarcopenia in Older Adults\u003c/strong\u003e. \u003cem\u003eChest \u003c/em\u003e2024, \u003cstrong\u003e166\u003c/strong\u003e(6):1476-1486.\u003c/li\u003e\n\u003cli\u003eZhang J, Xu G, Xu L: \u003cstrong\u003eNumber of Teeth and Denture Use Are Associated with Frailty among Chinese Older Adults: A Cohort Study Based on the CLHLS from 2008 to 2018\u003c/strong\u003e. \u003cem\u003eThe journal of nutrition, health \u0026amp; aging \u003c/em\u003e2023, \u003cstrong\u003e27\u003c/strong\u003e(11):972-979.\u003c/li\u003e\n\u003cli\u003eHuang G, Cao G: \u003cstrong\u003eTooth Loss Trajectories and Their Association with Functional Disability among Older Chinese Adults: Results from the Chinese Longitudinal Healthy Longevity Survey\u003c/strong\u003e. \u003cem\u003eJ Evid Based Dent Pract \u003c/em\u003e2022, \u003cstrong\u003e22\u003c/strong\u003e(4):101771.\u003c/li\u003e\n\u003cli\u003eZhang X, Zeng R, Ye D, Shi M, Zhu A, Chen L, Fan T, Zhu K, Xie F, Zhu W\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eTooth loss trajectories and their association with all-cause mortality among older Chinese adults\u003c/strong\u003e. \u003cem\u003eFront Oral Health \u003c/em\u003e2025, \u003cstrong\u003e6\u003c/strong\u003e:1535708.\u003c/li\u003e\n\u003cli\u003eChakraborty T, Kaper MS, Almansa J, Schuller AA, Reijneveld SA: \u003cstrong\u003eHealth literacy, oral diseases, and contributing pathways: results from the Lifelines Cohort Study\u003c/strong\u003e. \u003cem\u003eJournal of dentistry \u003c/em\u003e2025, \u003cstrong\u003e153\u003c/strong\u003e:105530.\u003c/li\u003e\n\u003cli\u003eYu J, Qin W, Huang W, Thomas K: \u003cstrong\u003eOral Health and Mortality Among Older Adults: A Doubly Robust Survival Analysis\u003c/strong\u003e. \u003cem\u003eAm J Prev Med \u003c/em\u003e2023, \u003cstrong\u003e64\u003c/strong\u003e(1):9-16.\u003c/li\u003e\n\u003cli\u003eZhao N, Teles F, Lu J, Koestler DC, Beck J, Boerwinkle E, Bressler J, Kelsey KT, Platz EA, Michaud DS: \u003cstrong\u003eEpigenome-wide association study using peripheral blood leukocytes identifies genomic regions associated with periodontal disease and edentulism in the Atherosclerosis Risk in Communities study\u003c/strong\u003e. \u003cem\u003eJournal of clinical periodontology \u003c/em\u003e2023, \u003cstrong\u003e50\u003c/strong\u003e(9):1140-1153.\u003c/li\u003e\n\u003cli\u003eSmith C, Woessner MN, Sim M, Levinger I: \u003cstrong\u003eSarcopenia definition: Does it really matter? 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cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(n=17099)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSarcopenia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo(n=9853)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes(n=2557)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEdentulism(n,%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e15478(91.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e9259(94.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e2005(78.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e1494( 8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e588(6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e548(21.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge(\u003c/strong\u003e\u003cstrong\u003eyears,\u003c/strong\u003e\u003cstrong\u003emedian[IQR])\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e58.0[51.0,65.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e57.0[50.0,63.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e67.0[62.0,74.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI(\u003c/strong\u003e\u003cstrong\u003ekg/m\u003csup\u003e2\u003c/sup\u003e,\u003c/strong\u003e\u003cstrong\u003emedian[IQR])\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e23.1[20.8,25.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e24.3[22.3,26.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e19.7[18.3,21.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex(n,%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e8747(51.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e4397(44.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e1825(71.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e8352(48.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e5456(55.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e732(28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidence(n,%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRural\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e10149(59.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e5882(59.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e1859(72.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUrban\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e6950(40.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e3971(40.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e698(27.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status(n,%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarried and living with a spouse\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e13676(80.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e8427(85.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e1769(69.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarried but living without a spouse\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e1177(6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e451(4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e70(2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSingle, divorced, and windowed\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e2224(13.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e975(9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e718(28.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation Status(n,%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eElementary school or below\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e11363(66.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e6241(63.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e2295(89.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMiddle school or above\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e5730(33.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e3612(36.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e262(10.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking_Status(n,%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-smoker\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e10117(59.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e5499(55.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e1749(68.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoker\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e6845(40.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e4347(44.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e804 (31.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrinking Status(n,%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrink but less than once a month\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e1335(8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e844(9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e140(5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrink more than once a month\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e3143(19.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e2257(24.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e294(12.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-drinker\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e11306(71.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e6233(66.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e1982(82.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegional Category(n,%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEast\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e6054(35.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e3646(37.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e704(27.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMidland\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e6203(36.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e3575(36.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e977(38.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWest\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e4835(28.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e2630(26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e876(34.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWC(\u003c/strong\u003e\u003cstrong\u003ecm,\u003c/strong\u003e\u003cstrong\u003emedian[IQR])\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e84.5[77.6,92.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e87.4[81.0,94.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e77.0[72.0,83.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTG(\u003c/strong\u003e\u003cstrong\u003emg/dL,\u003c/strong\u003e\u003cstrong\u003emedian[IQR])\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e106.2[75.2,156.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e109.7[77.0,163.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e94.7[69.9,131.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHDL(\u003c/strong\u003e\u003cstrong\u003emg/dL,\u003c/strong\u003e\u003cstrong\u003emedian[IQR])\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e49.1[39.9,59.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e47.6[39.0,57.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e55.7[45.6,66.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFBG(\u003c/strong\u003e\u003cstrong\u003emg/dL,\u003c/strong\u003e\u003cstrong\u003emedian[IQR])\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e102.6[94.5,113.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e103.1[95.2,115.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e101.2[93.6,111.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSBP(\u003c/strong\u003e\u003cstrong\u003emmHg,\u003c/strong\u003e\u003cstrong\u003emedian[IQR])\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e127.0[114.0,142.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e127.0[115.0,142.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e128.5[114.0,146.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDBP(\u003c/strong\u003e\u003cstrong\u003emmHg\u003c/strong\u003e\u003cstrong\u003e[IQR])\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e74.5[67.0,83.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e76.0[68.0,84.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e72.0[64.0,79.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCRP(\u003c/strong\u003e\u003cstrong\u003emmol/L,\u003c/strong\u003e\u003cstrong\u003e[IQR])\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e1.0[0.6,2.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e1.1[0.6,2.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e0.9[0.5,2.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eASMM(\u003c/strong\u003e\u003cstrong\u003ekg/m\u003csup\u003e2\u003c/sup\u003e,\u003c/strong\u003e\u003cstrong\u003emedian[IQR])\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e17.0[13.8,20.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e18.5[15.5,21.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e12.2[10.7,15.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eHDL, high density lipoprotein; FBG, fasting blood glucose; SBP, systolic blood pressure; DBP, diastolic blood pressure; CRP, C reactive protein.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2 The results of cross-sectional analysis for Wave 1 data.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEstimate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStatistic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e.value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 532px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-PSM\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e1.359\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e23.122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e2.363\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0.119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e2.273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 532px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePSM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e3.570\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.393\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e3.880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e0.453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e2.882\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eModel 1 represented the unadjusted crude association analysis;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eModel 2 adjusted for basic demographic characteristics including age, gender, urban-rural residence, education level, and marital status;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eModel 3 further adjusted for lifestyle factors (smoking, alcohol consumption), regional classification, and metabolic and inflammatory indicators (waist circumference, triglycerides, high-density lipoprotein, fasting blood glucose, systolic pressure, diastolic pressure, and C-reactive protein) based on Model 2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePSM, propensity score matching; SE, standard error.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3 The results of Longitudinal analysis for Wave 1-3 data.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"522\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEstimate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStatistic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e.value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 522px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-PSM\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eModel 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26.781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eModel 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eModel 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.221\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 522px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePSM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eModel 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.860\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eModel 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.866\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eModel 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.645\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eModel 1 represented the unadjusted crude association analysis;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eModel 2 adjusted for basic demographic characteristics including age, gender, urban-rural residence, education level, and marital status;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eModel 3 further adjusted for lifestyle factors (smoking, alcohol consumption), regional classification, and metabolic and inflammatory indicators (waist circumference, triglycerides, high-density lipoprotein, fasting blood glucose, systolic pressure, diastolic pressure, and C-reactive protein) based on Model 2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePSM, propensity score matching; SE, standard error.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-oral-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ohea","sideBox":"Learn more about [BMC Oral Health](http://bmcoralhealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ohea/default.aspx","title":"BMC Oral Health","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"edentulism, sarcopenia, oral health, ageing, longitudinal cohort, propensity-score matching","lastPublishedDoi":"10.21203/rs.3.rs-6637114/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6637114/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eEdentulism and sarcopenia are two highly prevalent, age-related conditions that share common nutritional, inflammatory, and functional pathways. Whether tooth loss independently contributes to the development of sarcopenia\u0026mdash;and in which population strata this effect is strongest\u0026mdash;remains uncertain, especially in Asian cohorts.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe analysed 17,099 participants (baseline 2011) from the China Health and Retirement Longitudinal Study (CHARLS). Sarcopenia was defined by Asian Working Group for Sarcopenia 2019 criteria. Multivariable logistic models (wave 1 cross-sectional) and Cox models (waves 1\u0026ndash;3 longitudinal, seven-year follow-up) were fitted sequentially: Model 1 (crude), Model 2 (plus demographic covariates), Model 3 (plus metabolic/ inflammatory factors). Propensity-score matching (PSM) was applied to minimise selection bias. Subgroup analyses covered sex, residence, marital status, education, smoking, drinking, and region. Sensitivity analyses tested robustness.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eEdentulism prevalence was 8.8%; sarcopenia prevalence, 15.0%. Cross-sectionally, edentulism increased sarcopenia risk in Model 1 (β\u0026thinsp;=\u0026thinsp;1.359, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and remained significant after full adjustment (β\u0026thinsp;=\u0026thinsp;0.271, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.023). In the PSM set, the effect strengthened (Model 3 β\u0026thinsp;=\u0026thinsp;0.453, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004). Longitudinally, edentulism predicted incident sarcopenia (Model 1 β\u0026thinsp;=\u0026thinsp;1.109, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001); significance attenuated after full adjustment (β\u0026thinsp;=\u0026thinsp;0.070, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.221) but re-emerged in PSM analyses (β\u0026thinsp;=\u0026thinsp;0.193, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008). Subgroup analyses showed consistently higher risks in males, rural residents, low-education groups, non-smokers, non-drinkers, and western regions.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eEdentulism is a robust, independent marker of elevated sarcopenia risk in Chinese adults, with particularly strong effects in socio-economically vulnerable subgroups. Routine oral-health screening should be integrated into geriatric assessments to identify patients at high risk for sarcopenia.\u003c/p\u003e","manuscriptTitle":"Edentulism as an Independent Risk Factor for Sarcopenia: Evidence from Cross-sectional and Longitudinal Analyses Based on the CHARLS Cohort","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-03 07:54:06","doi":"10.21203/rs.3.rs-6637114/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-09T07:23:41+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-08T02:49:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"160698887981963268408270390120222395010","date":"2025-09-05T03:33:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-27T07:08:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"274271057943475502241108806292021903913","date":"2025-08-25T02:17:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"333539667377123129915584502270089635317","date":"2025-08-22T03:31:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-30T13:44:34+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-05-19T19:48:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-17T06:47:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-17T06:45:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Oral Health","date":"2025-05-11T01:11:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-oral-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ohea","sideBox":"Learn more about [BMC Oral Health](http://bmcoralhealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ohea/default.aspx","title":"BMC Oral Health","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8afaa3bb-41c4-4ec8-8b46-ab8f8d3c0822","owner":[],"postedDate":"June 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-08T16:00:03+00:00","versionOfRecord":{"articleIdentity":"rs-6637114","link":"https://doi.org/10.1186/s12903-025-07430-z","journal":{"identity":"bmc-oral-health","isVorOnly":false,"title":"BMC Oral Health"},"publishedOn":"2025-12-02 15:57:18","publishedOnDateReadable":"December 2nd, 2025"},"versionCreatedAt":"2025-06-03 07:54:06","video":"","vorDoi":"10.1186/s12903-025-07430-z","vorDoiUrl":"https://doi.org/10.1186/s12903-025-07430-z","workflowStages":[]},"version":"v1","identity":"rs-6637114","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6637114","identity":"rs-6637114","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}